Brouri, A. (2016) Wiener-Hammerstein models identification. International Journal of Mathematical Models and Methods in Applied Sciences, 10. pp. 244-250.

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Abstract

This work discusses the identification of nonlinear systems structured in blocks. Presently, the proposed method is addressed to Wiener-Hammerstein models. Hammerstein and Wiener models are nonlinear representations of systems composed by connecting of a nonlinearity element f(.) and a linear subsystem G(s) in the form f(.)-G(s) and G(s)-f(.) respectively. The identification of nonlinearity blocks and linear subsystems is not a trivial problem, and has attracted a lot of research interest. The linear subsystems Gi(s) and Go(s) are allowed to be nonparametric and of unknown structure. Presently, the system nonlinearity is static and may be noninvertible. Moreover, this latter is of unknown structure and is only supposed to be well approximated, within any subinterval belonging to the working interval, with a polynomial of unknown order and parameters. Then, using a frequency identification method, a two-phase algorithm is presented for identifying the linear subsystems Gi(s) and Go(s) (the frequency complex gains) and the nonlinearity element f(.). The procedure is illustrated with simulated and experimental data. The proposed strategy involves simples input signals. © 2016, North Atlantic University Union NAUN. All rights reserved.

Item Type: Article
Subjects: Mathematics
Divisions: SCIENTIFIC PRODUCTION > Mathematics
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:48
URI: http://eprints.umi.ac.ma/id/eprint/4000

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